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PERTURB: Stata module to evaluate collinearity and ill-conditioning

Author

Listed:
  • John Hendrickx

    (University of Nijmegen)

Programming Language

Stata

Abstract

perturb is a tool for assessing the impact of small random changes (perturbations) to variables on parameter estimates. It is an alternative for collinearity diagnostics such as vif, collin, coldiag, coldiag2. perturb is particularly useful for evaluating collinearity if interactions are present or nonlinear transformations of variables, e.g. a squared term. peturb can show how the perturbations affect the estimates of a variable and terms derived from it whereas other collinearity diagnostics simply treat interactions and transformations as regular independent variables. perturb is not limited to linear regression but can be used for all regression-like models. perturb can also deal with categorical variables by randomly misclassifying them to assess the impact on parameter estimates.

Suggested Citation

  • John Hendrickx, 2004. "PERTURB: Stata module to evaluate collinearity and ill-conditioning," Statistical Software Components S445201, Boston College Department of Economics, revised 09 Dec 2004.
    • Handle: RePEc:boc:bocode:s445201
    Note: This module should be installed from within Stata by typing "ssc install perturb". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
    as

    Download full text from publisher

    File URL: http://fmwww.bc.edu/repec/bocode/p/perturb.ado
    File Function: program code
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/p/perturb.hlp
    File Function: help file
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/r/reclass.ado
    File Function: program code
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/r/reclass.hlp
    File Function: help file
    Download Restriction: no
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